Background: In chronic liver disease, fat and fibroinflammatory changes often coexist. However, their biomarkers, proton density fat fraction (PDFF) and T₁, are typically assessed separately. Their reproducibility under mutual confounding remains unclear. Purpose: To assess multicenter, multi-vendor reproducibility of confounder-corrected chemical shift-encoded (CSE)-MRI-based PDFF mapping and MOLLI-based T₁ mapping using a combined PDFF-T₁ phantom. Study Type: Prospective phantom study. Phantom: Commercial PDFF-T₁ Phantom (Model 725) with varying PDFF (0%–30%) and T₁ (200–1400 ms) values. Field Strength/Sequence: 1.5 T and 3 T multi-echo, three-dimensional spoiled-gradient-echo (SGRE) sequence for PDFF mapping, and MOLLI sequence (5(3)3 acquisition scheme) using two-dimensional SGRE readouts for T₁ mapping across four centers and vendors. Assessment: PDFF and T₁ maps were acquired using standardized protocols. PDFF maps were reconstructed locally, while T₁ maps were generated using a centralized algorithm. All maps were quantitatively analyzed by a single radiologist using standardized region-of-interest placement. Phantom temporal stability was assessed at one center across five sessions over 9 months (baseline, retest, 1 week, 6 and 9 months). Statistical Tests: Intraclass correlation coefficients (ICC), reproducibility coefficients (RDC), and linear regression analysis were used. A p value < 0.05 was considered statistically significant. Results: PDFF showed overall excellent reproducibility (ICC = 0.987, RDC = 3.7%), with increased variability at higher T₁ values (RDC up to 7.9% at T₁ = 1400 ms). T₁ mapping showed good reproducibility in the absence of fat (RDC 16–161 ms at PDFF = 0%), but moderate to poor reproducibility in the presence of fat, with RDC increasing up to 1553 ms at PDFF 30%. Temporal stability was excellent ICC ≥ 0.998 for both PDFF and T₁, and RDC of 1.1%–1.3% for PDFF and 52–57 ms for T₁. Data Conclusion: This phantom study demonstrated high reproducibility of PDFF, whereas T₁ reproducibility deteriorated at higher fat and T₁ levels, underscoring the need for fat-corrected T₁ mapping for reliable assessment of fibroinflammatory changes. Evidence Level: N/A. Technical Efficacy: Stage 1.

The 28th Annual Scientific Sessions of the Society for Cardiovascular Magnetic Resonance (SCMR) took place from January 29 to February 1, 2025, in Washington, D.C. SCMR 2025 brought together a diverse group of 1714 cardiologists, radiologists, scientists, and technologists from more than 80 countries to discuss emerging trends and the latest developments in cardiovascular magnetic resonance (CMR). The conference centered on the theme “Leading the Way to Accessible, Sustainable, and Efficient CMR,” highlighting innovations aimed at making CMR more clinically efficient, widely accessible, and environmentally sustainable. The program featured 728 abstracts and case presentations with an acceptance rate of 86% (728/849), including early career award abstracts, oral abstracts, oral cases and rapid-fire sessions, covering a broad range of CMR topics. It also offered engaging invited lectures across eight main parallel tracks and included four plenary sessions, two gold medalists, and one keynote speaker, with a total of 826 faculty participating. Focused sessions on accessibility, efficiency, and sustainability provided a platform for discussing current challenges and exploring future directions, while the newly introduced CMR Innovations Track showcased innovative session formats and fostered greater collaboration between researchers, clinicians, and industry. For the first time, SCMR 2025 also offered the opportunity for attendees to obtain CMR Level 1 Training Verification, integrated into the program. Additionally, expert case reading sessions and hands-on interactive workshops allowed participants to engage with real-world clinical scenarios and deepen their understanding through practical experience. Key highlights included plenary sessions on a variety of important topics, such as expanding boundaries, health equity, women's cardiovascular disease and a patient-clinician testimonial that emphasized the profound value of patient-centered research and collaboration. The scientific sessions covered a wide range of topics, from clinical applications in cardiomyopathies, congenital heart disease, and vascular imaging to women's heart health and environmental sustainability. Technical topics included novel reconstruction, motion correction, quantitative CMR, contrast agents, novel field strengths, and artificial intelligence applications, among many others. This paper summarizes the key themes and discussions from SCMR 2025, highlighting the collaborative efforts that are driving the future of CMR and underscoring the Society's unwavering commitment to research, education, and clinical excellence.

To evaluate heart rate as a patient-related confounder in a commonly applied T2 balanced steady-state free precession (bSSFP) mapping sequence used for myocardial tissue characterization.Materials and Methods: This retrospective analysis included prospectively (from December 2013 to November 2021) acquired cardiac MRI (1.5 T) datasets with T2 bSSFP mapping from 69 healthy volunteers. Phantom studies and Bloch simulations were performed with heart rates of 60–130 beats per minute and different resting periods (three, six, or nine R-R intervals). Sequence parameters (repetition time, echo time, flip angle, echo train length) were matched across volunteer, phantom, and simulation measurements. Reference values covered clinically relevant T1 and T2 properties found in native myocardium (short, 1041 and 44 msec; medium, 1293 and 43 msec; long, 1534 and 40 msec). A mixed linear model assessed the effect of heart rate on T2 values in volunteer measurements.Results: The study included 69 healthy volunteers (median age, 34 years; 44 female and 25 male). Heart rate influenced T2 values acquired with three R-R resting periods (r = −0.38, P =.002; linear regression slope, −0.7 msec/10 beats per minute [95% CI: −1.2, −0.1]). In simulation and phantom measurements, T2 values acquired with three R-R resting periods strongly correlated with heart rate, irrespective of myocardial T1 and T2 properties (r ≤ −0.88; P <.01 for all measurements). Heart rate dependency was reduced with increased resting periods in simulations and phantom measurements. Short myocardial T1 and T2 values derived from T2 bSSFP with nine R-R resting periods were not dependent on heart rate (r = −0.41; P =.33).Conclusion: T2 bSSFP with three R-R resting periods underestimates T2 values with increasing heart rates. Use of longer resting periods with T2 bSSFP mapping sequences reduced heart rate dependency.

Presenting quantitative data using non-standardized color maps potentially results in unrecognized misinterpretation of data. Clinically meaningful color maps should intuitively and inclusively represent data without misleading interpretation. Uniformity of the color gradient for color maps is critically important. Maximal color and lightness contrast, readability for color vision-impaired individuals, and recognizability of the color scheme are highly desirable features. This article describes the use of color maps in five key quantitative MRI techniques: relaxometry, diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE)-MRI, MR elastography (MRE), and water-fat MRI. Current display practice of color maps is reviewed and shortcomings against desirable features are highlighted. Evidence Level: 5. Technical Efficacy: Stage 2.

Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically “all-in-one” CMR, where several contrasts and/or motion states are acquired simultaneously, and “real-time” CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR. To this end, the vision of each is described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 will tackle the “all-in-one” approaches, and Part 2 the “real-time” approaches along with an overall summary of these emerging methods.

Purpose: The aim of this study is to develop and optimize an adiabatic (Formula presented.) ((Formula presented.)) mapping method for robust quantification of spin-lock (SL) relaxation in the myocardium at 3T. Methods: Adiabatic SL (aSL) preparations were optimized for resilience against (Formula presented.) and (Formula presented.) inhomogeneities using Bloch simulations. Optimized (Formula presented.) -aSL, Bal-aSL and (Formula presented.) -aSL modules, each compensating for different inhomogeneities, were first validated in phantom and human calf. Myocardial (Formula presented.) mapping was performed using a single breath-hold cardiac-triggered bSSFP-based sequence. Then, optimized (Formula presented.) preparations were compared to each other and to conventional SL-prepared (Formula presented.) maps (RefSL) in phantoms to assess repeatability, and in 13 healthy subjects to investigate image quality, precision, reproducibility and intersubject variability. Finally, aSL and RefSL sequences were tested on six patients with known or suspected cardiovascular disease and compared with LGE, (Formula presented.), and ECV mapping. Results: The highest (Formula presented.) preparation efficiency was obtained in simulations for modules comprising 2 HS pulses of 30 ms each. In vivo (Formula presented.) maps yielded significantly higher quality than RefSL maps. Average myocardial (Formula presented.) values were 183.28 (Formula presented.) 25.53 ms, compared with 38.21 (Formula presented.) 14.37 ms RefSL-prepared (Formula presented.). (Formula presented.) maps showed a significant improvement in precision (avg. 14.47 (Formula presented.) 3.71% aSL, 37.61 (Formula presented.) 19.42% RefSL, p < 0.01) and reproducibility (avg. 4.64 (Formula presented.) 2.18% aSL, 47.39 (Formula presented.) 12.06% RefSL, p < 0.0001), with decreased inter-subject variability (avg. 8.76 (Formula presented.) 3.65% aSL, 51.90 (Formula presented.) 15.27% RefSL, p < 0.0001). Among aSL preparations, (Formula presented.) -aSL achieved the better inter-subject variability. In patients, (Formula presented.) -aSL preparations showed the best artifact resilience among the adiabatic preparations. (Formula presented.) times show focal alteration colocalized with areas of hyper-enhancement in the LGE images. Conclusion: Adiabatic preparations enable robust in vivo quantification of myocardial SL relaxation times at 3T.

T₂-hyperintense lesions are the key imaging marker of multiple sclerosis (MS). Previous studies have shown that the white matter surrounding such lesions is often also affected by MS. Our aim was to develop a new method to visualize and quantify the extent of white matter tissue changes in MS based on relaxometry properties. We applied a fast, multi-parametric quantitative MRI approach and used a multi-component MR Fingerprinting (MC-MRF) analysis. We assessed the differences in the MRF component representing prolongedrelaxation time between patients with MS and controls and studied the relation between this component's volume and structural white matter damage identified on FLAIR MRI scans in patients with MS. A total of 48 MS patients at two different sites and 12 healthy controls were scanned with FLAIR and MRF-EPI MRI scans. MRF scans were analyzed with a joint-sparsity multi-component analysis to obtain magnetization fraction maps of different components, representing tissues such as myelin water, white matter, gray matter and cerebrospinal fluid. In the MS patients, an additional component was identified with increased transverse relaxation times compared to the white matter, likely representing changes in free water content. Patients with MS had a higher volume of the long- component in the white matter of the brain compared to healthy controls (B (95%-CI) = 0.004 (0.0006–0.008), p = 0.02). Furthermore, this MRF component had a moderate correlation (correlation coefficient R 0.47) with visible structural white matter changes on the FLAIR scans. Also, the component was found to be more extensive compared to structural white matter changes in 73% of MS patients. In conclusion, our MRF acquisition and analysis captured white matter tissue changes in MS patients compared to controls. In patients these tissue changes were more extensive compared to visually detectable white matter changes on FLAIR scans. Our method provides a novel way to quantify the extent of white matter changes in MS patients, which is underestimated using only conventional clinical MRI scans.

Objective: Quantitative Magnetic Resonance Imaging (MRI) holds great promise for the early detection of cartilage deterioration. Here, a Magnetic Resonance Fingerprinting (MRF) framework is proposed for comprehensive and rapid quantification of T ₁, T ₂ ^∗, and T _RAFF2 with whole-knee coverage. Methods: A MRF framework was developed to achieve quantification of Relaxation Along a Fictitious Field in the 2nd rotating frame of reference (T _RAFF2) along with T ₁ and T ₂ ^∗. The proposed sequence acquires 65 measurements of 25 high-resolution slices, interleaved with 7 inversion pulses and 40 RAFF2 trains, for whole-knee quantification in a total acquisition time of 3:25 min. Comparison with reference T ₁, T ₂ ^∗, and T _RAFF2 methods was performed in phantom and in seven healthy subjects at 3 T. Repeatability (test-retest) with and without repositioning was also assessed. Results: Phantom measurements resulted in good agreement between MRF and the reference with mean biases of -54, 2, and 5 ms for T ₁, T ₂ ^∗, and T _RAFF2, respectively. Complete characterization of the whole-knee cartilage was achieved for all subjects, and, for the femoral and tibial compartments, a good agreement between MRF and reference measurements was obtained. Across all subjects, the proposed MRF method yielded acceptable repeatability without repositioning (R ²≥ 0.94) and with repositioning (R ²≥ 0.57) for T ₁, T ₂ ^∗, and T _RAFF2. Significance: The short scan time combined with the whole-knee coverage makes the proposed MRF framework a promising candidate for the early assessment of cartilage degeneration with quantitative MRI, but further research may be warranted to improve repeatability after repositioning and assess clinical value in patients.

The aim of this study is to develop and evaluate a regularized Simultaneous Multi-Slice (SMS) reconstruction method for improved Cardiac Magnetic Resonance Imaging (CMR). The proposed reconstruction method, SMS with COmpOsition of k-space IntErpolations (SMS-COOKIE) combines the advantages of Iterative Self-consistent Parallel Imaging Reconstruction (SPIRiT) and split slice-Generalized Autocalibrating Partially Parallel Acquisitions (GRAPPA), while allowing regularization for further noise reduction. The proposed SMS-COOKIE was implemented with and without regularization, and validated using a Saturation Pulse-Prepared Heart rate Independent inversion REcovery (SAPPHIRE) myocardial T ₁ mapping sequence. The performance of the proposed reconstruction method was compared to ReadOut (RO)–SENSE-GRAPPA and split slice-GRAPPA, on both retrospectively and prospectively three-fold SMS-accelerated data with an additional two-fold in-plane acceleration. All SMS reconstruction methods yielded similar T ₁ values compared to single band imaging. SMS-COOKIE showed lower spatial variability in myocardial T ₁ with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10 ⁻⁴). The proposed method with additional locally low rank (LLR) regularization reduced the spatial variability, again with significant improvement over RO-SENSE-GRAPPA and split slice-GRAPPA (P < 10 ⁻⁴). In conclusion, improved reconstruction quality was achieved with the proposed SMS-COOKIE, which also provided lower spatial variability with significant improvement over split slice-GRAPPA.

Purpose: To investigate and mitigate the influence of physiological and acquisition-related parameters on myocardial blood flow (MBF) measurements obtained with myocardial Arterial Spin Labeling (myoASL). Methods: A Flow-sensitive Alternating Inversion Recovery (FAIR) myoASL sequence with bSSFP and spoiled GRE (spGRE) readout is investigated for MBF quantification. Bloch-equation simulations and phantom experiments were performed to evaluate how variations in acquisition flip angle (FA), acquisition matrix size (AMS), heart rate (HR) and blood (Formula presented.) relaxation time ((Formula presented.)) affect quantification of myoASL-MBF. In vivo myoASL-images were acquired in nine healthy subjects. A corrected MBF quantification approach was proposed based on subject-specific (Formula presented.) values and, for spGRE imaging, subtracting an additional saturation-prepared baseline from the original baseline signal. Results: Simulated and phantom experiments showed a strong dependence on AMS and FA ((Formula presented.) >0.73), which was eliminated in simulations and alleviated in phantom experiments using the proposed saturation-baseline correction in spGRE. Only a very mild HR dependence ((Formula presented.) >0.59) was observed which was reduced when calculating MBF with individual (Formula presented.). For corrected spGRE, in vivo mean global spGRE-MBF ranged from 0.54 to 2.59 mL/g/min and was in agreement with previously reported values. Compared to uncorrected spGRE, the intra-subject variability within a measurement (0.60 mL/g/min), between measurements (0.45 mL/g/min), as well as the inter-subject variability (1.29 mL/g/min) were improved by up to 40% and were comparable with conventional bSSFP. Conclusion: Our results show that physiological and acquisition-related factors can lead to spurious changes in myoASL-MBF if not accounted for. Using individual (Formula presented.) and a saturation-baseline can reduce these variations in spGRE and improve reproducibility of FAIR-myoASL against acquisition parameters.

Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality, causing over 17. 9 million deaths worldwide per year with associated costs of over $800 billion. Improving prevention, diagnosis, and treatment of CVD is therefore a global priority. Cardiovascular magnetic resonance (CMR) has emerged as a clinically important technique for the assessment of cardiovascular anatomy, function, perfusion, and viability. However, diversity and complexity of imaging, reconstruction and analysis methods pose some limitations to the widespread use of CMR. Especially in view of recent developments in the field of machine learning that provide novel solutions to address existing problems, it is necessary to bridge the gap between the clinical and scientific communities. This review covers five essential aspects of CMR to provide a comprehensive overview ranging from CVDs to CMR pulse sequence design, acquisition protocols, motion handling, image reconstruction and quantitative analysis of the obtained data. (1) The basic MR physics of CMR is introduced. Basic pulse sequence building blocks that are commonly used in CMR imaging are presented. Sequences containing these building blocks are formed for parametric mapping and functional imaging techniques. Commonly perceived artifacts and potential countermeasures are discussed for these methods. (2) CMR methods for identifying CVDs are illustrated. Basic anatomy and functional processes are described to understand the cardiac pathologies and how they can be captured by CMR imaging. (3) The planning and conduct of a complete CMR exam which is targeted for the respective pathology is shown. Building blocks are illustrated to create an efficient and patient-centered workflow. Further strategies to cope with challenging patients are discussed. (4) Imaging acceleration and reconstruction techniques are presented that enable acquisition of spatial, temporal, and parametric dynamics of the cardiac cycle. The handling of respiratory and cardiac motion strategies as well as their integration into the reconstruction processes is showcased. (5) Recent advances on deep learning-based reconstructions for this purpose are summarized. Furthermore, an overview of novel deep learning image segmentation and analysis methods is provided with a focus on automatic, fast and reliable extraction of biomarkers and parameters of clinical relevance.